During the production of a multiplicity of chips, attempts are often made to deduce deviation patterns from test results of tested chips in a computer-aided manner, from which deviation patterns possible deviation causes in the production process can subsequently be inferred.
In this context, a method of so-called blind source separation is conventionally used, in which a matrix factorization is carried out by a maximum likelihood optimization method. However, this method takes into account only for exactly one test whether or not a chip has passed this test.
In practice, however, a plurality of tests or measurements are carried out, which cannot be taken into account in the context of the conventional maximum likelihood optimization method.